Electroencephalogram-Driven Machine-Learning Scenario for Assessing Impulse Control Disorder Comorbidity in Parkinson's Disease Using a Low-Cost, Custom LEGO-Like Headset.

Patients with Parkinson's disease (PD) may develop cognitive symptoms of impulse control disorders (ICDs) when chronically treated with dopamine agonist (DA) therapy for motor deficits. Motor and cognitive comorbidities critically increase the disability and mortality of the affected patients. This study proposes an electroencephalogram (EEG)-driven machine-learning scenario to automatically assess ICD comorbidity in PD. We employed a classic Go/NoGo task to appraise the capacity of cognitive and motoric inhibition with a low-cost, custom LEGO-like headset to record task-relevant EEG activity. Further, we optimized a support vector machine (SVM) and support vector regression (SVR) pipeline to learn discriminative EEG spectral signatures for the detection of ICD comorbidity and the estimation of ICD severity, respectively. With a dataset of 21 subjects with typical PD, 9 subjects with PD and ICD comorbidity (ICD), and 25 healthy controls (HC), the study results showed that the SVM pipeline differentiated subjects with ICD from subjects with PD with an accuracy of 66.3% and returned an around-chance accuracy of 53.3% for the classification of PD versus HC subjects without the comorbidity concern. Furthermore, the SVR pipeline yielded significantly higher severity scores for the ICD group than for the PD group and resembled the ICD vs. PD distinction according to the clinical questionnaire scores, which was barely replicated by random guessing. Without a commercial, high-precision EEG product, our demonstration may facilitate deploying a wearable computer-aided diagnosis system to assess the risk of DA-triggered cognitive comorbidity in patients with PD in their daily environment.

Cost-efficient and Custom Electrode-holder Assembly Infrastructure for EEG Recordings.

Mobile electroencephalogram (EEG)-sensing technologies have rapidly progressed and made the access of neuroelectrical brain activity outside the laboratory in everyday life more realistic. However, most existing EEG headsets exhibit a fixed design, whereby its immobile montage in terms of electrode density and coverage inevitably poses a great challenge with applicability and generalizability to the fundamental study and application of the brain-computer interface (BCI). In this study, a cost-efficient, custom EEG-electrode holder infrastructure was designed through the assembly of primary components, including the sensor-positioning ring, inter-ring bridge, and bridge shield. It allows a user to (re)assemble a compact holder grid to accommodate a desired number of electrodes only to the regions of interest of the brain and iteratively adapt it to a given head size for optimal electrode-scalp contact and signal quality. This study empirically demonstrated its easy-to-fabricate nature by a low-end fused deposition modeling (FDM) 3D printer and proved its practicability of capturing event-related potential (ERP) and steady-state visual-evoked potential (SSVEP) signatures over 15 subjects. This paper highlights the possibilities for a cost-efficient electrode-holder assembly infrastructure with replaceable montage, flexibly retrofitted in an unlimited fashion, for an individual for distinctive fundamental EEG studies and BCI applications.

Simultaneous assessment of cognitive function, circadian rhythm, and spontaneous activity in aging mice.

Cognitive function declines substantially with age in both humans and animal models. In humans, this decline is associated with decreases in independence and quality of life. Although the methodology for analysis of cognitive function in human models is relatively well established, similar analyses in animal models have many technical issues (e.g., unintended experimenter bias, motivational issues, stress, and testing during the light phase of the light dark cycle) that limit interpretation of the results. These caveats, and others, potentially bias the interpretation of studies in rodents and prevent the application of current tests of learning and memory as part of an overall healthspan assessment in rodent models of aging. The goal of this study was to establish the methodology to assess cognitive function in aging animals that addresses many of these concerns. Here, we use a food reward-based discrimination procedure with minimal stress in C57Bl/6J male mice at 6, 21, and 27 months of age, followed by a reversal task to assess behavioral flexibility. Importantly, the procedures minimize issues related to between-experimenter confounds and are conducted during both the dark and light phases of the light dark cycle in a home-cage setting. During cognitive testing, we were able to assess multiple measures of spontaneous movement and diurnal activity in young and aged mice including, distance moved, velocity, and acceleration over a 90-h period. Both initial discrimination and reversal learning significantly decreased with age and, similar to rats and humans, not all old mice demonstrated impairments in learning with age. These results permitted classification of animals based on their cognitive status. Analysis of movement parameters indicated decreases in distance moved as well as velocity and acceleration with increasing age. Based on these data, we developed preliminary models indicating, as in humans, a close relationship exists between age-related movement parameters and cognitive ability. Our results provide a reliable method for assessing cognitive performance with minimal stress and simultaneously provide key information on movement and diurnal activity. These methods represent a novel approach to developing non-invasive healthspan measures in rodent models that allow standardization across laboratories.

Assessment of Pharmaceutical Company and Device Manufacturer Payments to Gastroenterologists and Their Participation in Clinical Practice Guideline Panels.

Importance: Payments from pharmaceutical and device manufacturers to physicians may influence the advice physicians give patients and peers. Objectives: To investigate the nature and amounts of monetary and other benefits that gastroenterologists received and to determine the participation of those receiving benefits in the formulation of clinical practice guidelines. Design, Setting, and Participants: This cohort study analyzed information from the Centers for Medicare & Medicaid Services Open Payments database, including all reports about payments that pharmaceutical and device manufacturers gave to adult or pediatric gastroenterologists in 2016. PubMed was used to examine the professional affiliations and publication records of top payment recipients. Panelists of clinical guidelines who also received personal financial rewards listed in the Open Payments database were identified. Main Outcomes and Measures: Payments made to gastroenterologists by pharmaceutical company and device manufacturers. Results: Of 15 497 gastroenterologists, 13 467 (86.9%) received a total of 432 463 payments accounting for a total expenditure of $67 144 862. Direct financial payments for consultations, talks, or other services were made to 2055 physicians and were responsible for 4.2% of payments (18 179 of 432 463), but for 62.7% of total expenditures ($42 086 207 of $67 144 862). Although a significant number of submissions were for food and beverages, they constituted only a small amount of total expenditure. For gastroenterologists treating adult patients, 10 products were linked to 63.8% of payments (11 221 of 17 588) related to direct financial rewards and 37.1% of the total expenditures ($24 892 643 of $67 144 862). Twenty-nine of 36 clinical practice guidelines included panelists who had received honoraria or consultation fees from industry sources, with amounts exceeding $10 000 in 8 of them (22%). Conclusions and Relevance: Most gastroenterologists accept meals or gifts from industry, with 2055 of 15 497 gastroenterologists receiving direct payments and 8 of 36 clinical practice guidelines panelists having received more than $10 000. Considering the known impact of such benefits on prescribing patterns and other professional behaviors, policy makers should consider revising regulations governing interactions with industry and disclosure formats alerting others to their potential biasing impact.